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部署和取消部署应用

创建应用后，您必须部署该应用，才能流式传输和分析数据。

部署应用

使用所有必要组件构建端到端应用后，您必须部署该应用才能开始使用。

控制台

打开 Vertex AI Vision 信息中心的应用标签页。

前往“应用”标签页
从列表中选择应用名称旁边的查看应用。
在应用图表构建器页面中，点击部署按钮。
在随即打开的部署应用菜单中，选择任意选项，然后点击部署。

注意：如需详细了解启用输出流式传输选项，请参阅启用直播输出。如需详细了解为此应用启用监控选项，请参阅启用和使用应用监控。

部署完成后，节点旁边会显示绿色对勾标记。

REST 和命令行

如需部署应用以供使用，请使用 projects.locations.applications.deploy 方法发送 POST 请求。

在使用任何请求数据之前，请先进行以下替换：

PROJECT：您的 Google Cloud 项目 ID 或项目编号。
LOCATION_ID：您在其中使用 Vertex AI Vision 的区域。例如：us-central1、europe-west4。请参阅可用区域。
APPLICATION_ID：目标应用的 ID。

HTTP 方法和网址：

POST https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_ID:deploy

如需发送请求，请选择以下方式之一：

curl

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d "" \
     "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_ID:deploy"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -Uri "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_ID:deploy" | Select-Object -Expand Content

如果成功，请求会启动一个长时间运行的操作，并返回一个包含操作 ID 的 JSON 对象。

{
  "name": "projects/PROJECT_ID/locations/LOCATION_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": "YYYY-MM-DDTHH:MM:SS.454506987Z",
    "target": "projects/PROJECT_ID/locations/LOCATION_ID/applications/APPLICATION_ID",
    "verb": "update",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

获取操作状态

使用响应中的操作 ID 获取部署请求的状态。

在使用任何请求数据之前，请先进行以下替换：

REGIONALIZED_ENDPOINT：端点可能包含与 LOCATION_ID 匹配的前缀，例如 europe-west4-。详细了解区域级端点。
PROJECT_NUMBER：您的 Google Cloud 项目编号。
LOCATION_ID：您在其中使用 Vertex AI Vision 的区域。例如：us-central1、europe-west4。请参阅可用区域。
OPERATION_ID：启动长时间运行的操作时返回的操作 ID。例如：
- projects/123456/locations/us-central1/[...]/operations/OPERATION_ID

HTTP 方法和网址：

GET https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

响应

{
  "name": "projects/PROJECT_ID/locations/LOCATION_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": "2023-01-12T17:53:14.454506987Z",
    "endTime": "2023-01-12T17:53:22.979720545Z",
    "target": "projects/PROJECT_ID/locations/LOCATION_ID/applications/APPLICATION_NAME",
    "verb": "update",
    "statusMessage": "Instance Deployment Pending....",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.Application",
    "name": "projects/PROJECT_ID/locations/LOCATION_ID/applications/APPLICATION_NAME",
    "createTime": "2023-01-06T21:16:26.465867295Z",
    "updateTime": "2023-01-12T17:53:14.458441937Z",
    "displayName": "APPLICATION_NAME",
    "applicationConfigs": {
      "nodes": [
        {
          "name": "builtin-input-stream",
          "displayName": "Streams",
          "nodeConfig": {
            "videoStreamInputConfig": {}
          },
          "processor": "builtin:stream-input",
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-general-object-detector",
          "displayName": "Object detector",
          "nodeConfig": {
            "generalObjectDetectionConfig": {}
          },
          "processor": "builtin:general-object-detector",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            }
          ],
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-media-warehouse",
          "displayName": "Vision AI Warehouse",
          "nodeConfig": {
            "mediaWarehouseConfig": {
              "corpus": "projects/PROJECT_ID/locations/LOCATION_ID/corpora/CORPUS_ID"
            }
          },
          "processor": "builtin:media-warehouse",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            },
            {
              "parentNode": "builtin-general-object-detector"
            }
          ],
          "outputAllOutputChannelsToStream": false
        }
      ]
    },
    "runtimeInfo": {
      "deployTime": "2023-01-12T17:53:22.887918Z",
      "globalOutputResources": [
        {
          "outputResource": "projects/PROJECT_ID/locations/LOCATION_ID/corpora/CORPUS_ID/dataSchemas/stream-resource-name",
          "key": "stream-resource-name"
        },
        {
          "outputResource": "projects/PROJECT_ID/locations/LOCATION_ID/corpora/CORPUS_ID/dataSchemas/stream-display-name",
          "key": "stream-display-name"
        },
        {
          "outputResource": "projects/PROJECT_ID/locations/LOCATION_ID/corpora/CORPUS_ID/dataSchemas/stream-resource-id",
          "key": "stream-resource-id"
        },
        {
          "outputResource": "projects/PROJECT_ID/locations/LOCATION_ID/corpora/CORPUS_ID/dataSchemas/general-object-detection",
          "producerNode": "builtin-general-object-detector",
          "key": "general_object_detection_data_schema_id"
        }
      ]
    },
    "state": "DEPLOYED",
    "deploymentEnvironment": "DEPLOYMENT_ENVIRONMENT_CLOUD"
  }
}

取消部署应用

如需停止使用应用，您必须取消部署应用。

控制台

打开 Vertex AI Vision 信息中心的应用标签页。

前往“应用”标签页
从列表中选择应用名称旁边的查看应用。
在应用图表构建器页面中，点击停用按钮。

REST 和命令行

如需取消部署应用，请使用 projects.locations.applications.undeploy 方法发送 POST 请求。

在使用任何请求数据之前，请先进行以下替换：

PROJECT：您的 Google Cloud 项目 ID 或项目编号。
LOCATION_ID：您在其中使用 Vertex AI Vision 的区域。例如：us-central1、europe-west4。请参阅可用区域。
APPLICATION_ID：目标应用的 ID。

HTTP 方法和网址：

POST https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_ID:undeploy

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d "" \
     "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_ID:undeploy"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -Uri "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_ID:undeploy" | Select-Object -Expand Content

如果成功，请求会启动一个长时间运行的操作，并返回一个包含操作 ID 的 JSON 对象。

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": "2023-01-12T18:14:48.260296926Z",
    "target": "projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/APPLICATION_NAME",
    "verb": "update",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

获取操作状态

使用响应中的操作 ID 获取取消部署请求的状态。

在使用任何请求数据之前，请先进行以下替换：

REGIONALIZED_ENDPOINT：端点可能包含与 LOCATION_ID 匹配的前缀，例如 europe-west4-。详细了解区域级端点。
PROJECT_NUMBER：您的 Google Cloud 项目编号。
LOCATION_ID：您在其中使用 Vertex AI Vision 的区域。例如：us-central1、europe-west4。请参阅可用区域。
OPERATION_ID：启动长时间运行的操作时返回的操作 ID。例如：
- projects/123456/locations/us-central1/[...]/operations/OPERATION_ID

HTTP 方法和网址：

GET https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

响应

{
  "name": "projects/PROJECT_ID/locations/LOCATION_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": "2023-01-12T18:14:48.260296926Z",
    "endTime": "2023-01-12T18:14:58.059563424Z",
    "target": "projects/PROJECT_ID/locations/LOCATION_ID/applications/APPLICATION_NAME",
    "verb": "update",
    "statusMessage": "Instance Undeployment Pending....",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.Application",
    "name": "projects/PROJECT_ID/locations/LOCATION_ID/applications/APPLICATION_NAME",
    "createTime": "2023-01-06T21:16:26.465867295Z",
    "updateTime": "2023-01-12T18:14:48.264089325Z",
    "displayName": "APPLICATION_NAME",
    "applicationConfigs": {
      "nodes": [
        {
          "name": "builtin-input-stream",
          "displayName": "Streams",
          "nodeConfig": {
            "videoStreamInputConfig": {}
          },
          "processor": "builtin:stream-input",
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-general-object-detector",
          "displayName": "Object detector",
          "nodeConfig": {
            "generalObjectDetectionConfig": {}
          },
          "processor": "builtin:general-object-detector",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            }
          ],
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-media-warehouse",
          "displayName": "Vision AI Warehouse",
          "nodeConfig": {
            "mediaWarehouseConfig": {
              "corpus": "projects/PROJECT_ID/locations/LOCATION_ID/corpora/CORPUS_ID"
            }
          },
          "processor": "builtin:media-warehouse",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            },
            {
              "parentNode": "builtin-general-object-detector"
            }
          ],
          "outputAllOutputChannelsToStream": false
        }
      ]
    },
    "state": "CREATED",
    "deploymentEnvironment": "DEPLOYMENT_ENVIRONMENT_CLOUD"
  }
}

后续步骤

如需了解如何开始从应用的输入数据流中提取数据，请参阅创建和管理数据流。
如需了解如何在管理应用中列出应用和查看已部署应用的实例，请参阅相关文档。
如需了解如何从提取流或分析后的模型输出数据中读取应用输入数据，请参阅读取流数据。